Published on in Vol 7, No 3 (2021): March

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/25859, first published .
App Use and Usability of a Barcode-Based Digital Platform to Augment COVID-19 Contact Tracing: Postpilot Survey and Paradata Analysis

App Use and Usability of a Barcode-Based Digital Platform to Augment COVID-19 Contact Tracing: Postpilot Survey and Paradata Analysis

App Use and Usability of a Barcode-Based Digital Platform to Augment COVID-19 Contact Tracing: Postpilot Survey and Paradata Analysis

Journals

  1. Scherr T, Hardcastle A, Moore C, DeSousa J, Wright D. Understanding On-Campus Interactions With a Semiautomated, Barcode-Based Platform to Augment COVID-19 Contact Tracing: App Development and Usage. JMIR mHealth and uHealth 2021;9(3):e24275 View
  2. O'Connell J, Abbas M, Beecham S, Buckley J, Chochlov M, Fitzgerald B, Glynn L, Johnson K, Laffey J, McNicholas B, Nuseibeh B, O'Callaghan M, O'Keeffe I, Razzaq A, Rekanar K, Richardson I, Simpkin A, Storni C, Tsvyatkova D, Walsh J, Welsh T, O'Keeffe D. Best Practice Guidance for Digital Contact Tracing Apps: A Cross-disciplinary Review of the Literature. JMIR mHealth and uHealth 2021;9(6):e27753 View
  3. Buhr L, Schicktanz S, Nordmeyer E. Attitudes Toward Mobile Apps for Pandemic Research Among Smartphone Users in Germany: National Survey. JMIR mHealth and uHealth 2022;10(1):e31857 View
  4. Robin R, Dandis A. Business as usual through contact tracing app: what influences intention to download?. Journal of Marketing Management 2021;37(17-18):1903 View
  5. Dash S, Jain A, Dey L, Dasgupta T, Naskar A. Factors affecting user experience of contact tracing app during COVID-19: an aspect-based sentiment analysis of user-generated review. Behaviour & Information Technology 2023;42(2):249 View
  6. Vincent W. Developing and Evaluating a Measure of the Willingness to Use Pandemic-Related mHealth Tools Using National Probability Samples in the United States: Quantitative Psychometric Analyses and Tests of Sociodemographic Group Differences. JMIR Formative Research 2023;7:e38298 View
  7. AlAli E, AL-Dossary R, Al-Rayes S, Al-Ansary N, Alshawan D, Almulla S, Alanezi F, Alakrawi Z, Alnaim N, Saraireh L, Attar R, Alaenzi N, bin Hasher H, AlThani B, Alsulaiman L, Alenazi N, Hariri B, Alanzi T. Evaluation of the Patient Experience with the Mawid App during the COVID-19 Pandemic in Al Hassa, Saudi Arabia. Healthcare 2022;10(6):1008 View
  8. Ayalon O, Li S, Preneel B, Redmiles E. Not Only for Contact Tracing. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2022;6(4):1 View
  9. Saeidnia H, Karajizadeh M, Mohammadzadeh Z, Abdoli S, Hassanzadeh M. Usability Evaluation of the Mask Mobile Application: The Official Application of the Iranian Government. Iranian Journal of Medical Microbiology 2022;16(1):49 View
  10. Tao P, Liu N, Dong C. Research progress of MIoT and digital healthcare in the new era. Clinical eHealth 2024;7:1 View
  11. Garavand A, Ameri F, Salehi F, Talebi A, Karbasi Z, Sabahi A, Ortega A. A Systematic Review of Health Management Mobile Applications in COVID-19 Pandemic: Features, Advantages, and Disadvantages. BioMed Research International 2024;2024:1 View
  12. Cheung L, Lau A, Lam K, Ng P. A Review of Environmental Factors for an Ontology-Based Risk Analysis for Pandemic Spread. COVID 2024;4(4):466 View